The concept of new quality productive forces represents a distinct Chinese-style theoretical interpretation of Marxist advanced productive forces in the context of the new era. It also embodies a "Chinese solution" for translating Marxist theories into practice—aiming at promoting high-quality development, advancing Chinese-style modernization, and realizing the great rejuvenation of the Chinese nation—thereby underscoring its profound strategic significance. Grounded in disciplinary thinking, this article offered a theoretical interpretation and logical reflection on the geographical thinking and spatial logic of new quality productive forces in the new era. It further explored their practical pathways and responsive strategies in Northeast China under the orientation of the national framework of the "five major securities". The findings indicate that: 1) New quality productive forces embody the essential attributes of Marxist advanced productive forces and serve as an important tool for promoting high-quality urban and regional development. Their evolution follows the geographical logic of the temporal evolution view, human-environment coordination view, regional differentiation view, and industrial embodiment view. 2) The essence of new quality productive forces lies in the transformation from a mere technological tool attribute (means of production) toward serving and realizing urban-regional functional objectives (development goals). Within this process, industry acts as the core carrier, and the spatial realization of new quality productive forces follows a progressive, place-based logic of "problem identification→spatial restructuring→new industrial construction". 3) In the case of Northeast China, the development of new quality productive forces should be guided both by the strategic imperatives of the national "five major securities" and by the constraints of regional conditions and resource endowments. Following the same spatial logic of "problem identification→spatial restructuring→new industrial construction", this study systematically considered development approaches and policy strategies from the perspectives of both the overall region and its differentiated city types. Finally, the study emphasized that not all cities are equally suited for homogeneous development of new quality productive forces. Their advancement must align with local resource endowments and locational advantages, with industry serving as the practical carrier. By integrating the geographical perspectives of temporal evolution, human-environment coordination, regional differentiation, and industrial embodiment into the economic interpretation of the "advancement" of new quality productive forces, this research proposed a new paradigm for their spatial realization and materialization, offering theoretical insights for the revitalization and high-quality development of Northeast China.

In the context of the global technological revolution, artificial intelligence (AI) technology has emerged as a key driver of economic growth, with China leading the world in AI patent filings for five consecutive years, according to the World Intellectual Property Organization (WIPO) report. However, significant disparities in innovation levels persist across regions, and the level of collaborative innovation between regions still lags significantly behind that of developed countries. Inefficient and constrained channels for knowledge spillover are key limiting factors. This study focused on the Yangtze River Economic Belt as the research area. We selected 108 prefecture-level and above cities within this region as research objects to construct a city-level AI innovation cooperation network for the Yangtze River Economic Belt. Using social network analysis (SNA) and the exponential random graph model (ERGM), we examined the evolutionary characteristics of the network and analyzed the role of knowledge spillover in the development of the AI innovation cooperation network, incorporating city attributes, geographical proximity, and administrative proximity. The findings reveal the following key insights: 1) Evolution of Network Structure: Social network analysis indicated that the AI innovation cooperation network in the Yangtze River Economic Belt had evolved from a unipolar structure to a multi-polar balanced structure. Empirical analysis using the ERGM further confirmed that innovation resources such as knowledge and skills within the region were diffusing beyond their original boundaries, although core cities continued to dominate the pathways of knowledge spillover and maintain central positions in the network. 2) Knowledge Spillover's Driving Role: Knowledge spillover consistently played a crucial promoting role in the development of the innovation cooperation network, with its mode of influence transforming as the network evolves. Empirical analysis of the Yangtze River Economic Belt as a whole and its sub-regions revealed that in the early stages of AI development, knowledge spillover facilitated the formation of collaborative relationships. As the number of nodes and relationships grew, the effect of knowledge spillover somewhat diminished, but it remained a core influencing factor for the cooperation network. 3) Network Structural Evolution Trends: The network structure of AI innovation cooperation in the Yangtze River Economic Belt exhibited specific evolutionary trends. Overall, core-periphery structures and "closed triadic" structures significantly promoted network formation, while "open triadic" structures inhibited it. Specifically, regions in the early stages of AI development are more prone to forming core-periphery structures. As the number of nodes and relationships increases, the role of this structure gradually weakens, while the promoting effect of closed triadic structures becomes more pronounced. 4) Spatiotemporal Heterogeneity and Regional Development: Heterogeneity analysis showed that the impact of knowledge spillover on the AI innovation cooperation network exhibited significant spatiotemporal heterogeneity, and different regions displayed distinct endogenous network structure evolution characteristics. In the upstream region, the knowledge spillover effect became explicit after 2016, forming a core-periphery network structure. In the midstream region, the knowledge spillover effect is more pronounced, resulting in a hybrid network structure where direct cooperation and indirect cooperation coexist. In the downstream region, the knowledge spillover effect, while persistently significant, gradually faded away, leading to a polycentric network structure where cities are more likely to engage in direct rather than indirect cooperation.

Fostering emerging industries and accelerating the transition between old and new growth drivers are crucial for achieving high-quality economic development and enhancing international competitiveness, therefore it is necessary to deeply understand regional new industrial paths and its driving mechanisms. Taking the development zone, a fundamental unit derived from new industries, as the research object, an analytical framework was established for external linkages, endogenous processes, and new industrial paths. By quantitatively analyzing the enterprise registration data through the location quotient method, standard deviation ellipse method, and industrial linkage analysis method, and combining the qualitative materials obtained from field research, this study explored the path development and driving mechanisms of industrial evolution in the development zones of Jiangsu Province. The research revealed that the industrial evolution of development zones has undergone three stages: the implantation of local paths under the impact of globalization, the implantation of global paths under multi-scale links, and the diversified development of paths under endogenous innovation. As development zones evolved, the effect of external linkages shifted from path shaping in the early stages to path triggering in the later stages. Simultaneously, the focus of endogenous processes transitioned from absorption and learning to recombination and innovation. The synergistic evolution and interaction of these two aspects constituted the core driving mechanism for industrial diversification in the development zones. This study revealed the intrinsic logic of industrial catch-up and upgrading in China at the scale of development zones. It also enriched evolutionary economic geography's understanding of the paths and mechanisms of industrial evolution in emerging economies, thus providing insights for promoting regional industrial transformation and upgrading in the new era.

The spatial and temporal imbalance in the allocation of urban healthcare resources represents a major challenge to the implementation of the "Healthy China" strategy. Identifying dynamic changes in healthcare accessibility and their equity implications is crucial for optimizing healthcare resource distribution. Addressing the research gaps in quantifying the spatiotemporal coordination of multi-modal transportation and assessing the dynamic equity of accessibility across multiple time periods, this study developed a comprehensive evaluation framework. This framework integrates the Criteria Importance Through Intercriteria Correlation (CRITIC) weighting method, an enhanced two-step floating catchment area (2SFCA) method, and a time-based Gini coefficient. A case study of the main urban area of Kunming City was conducted, utilizing multi-period real-time traffic data to measure healthcare accessibility under both driving and subway-dominated public transport modes. The Multi-mode Accessibility Gap (MAG) index was employed to quantify the coordination between these two modes. The findings reveal three key points. First, the spatial pattern of healthcare accessibility is characterized by "central radiation with distance decay" for driving and "fragmentation along subway lines" for public transport. Second, reducing the time threshold significantly intensifies the spatial agglomeration of resources, as indicated by a time-based Gini coefficient reaching up to 0.968, which highlights substantial equity concerns. Third, the MAG analysis demonstrated a failure of modal complementarity in both the urban core and peripheral areas. The proposed framework offers a novel perspective for understanding the spatiotemporal equity of healthcare resources. It also provides a methodological reference for optimizing resource allocation in other similar cities.

Mountainous areas account for more than two-thirds of China's land area, and their complex geographical conditions pose significant challenges to disaster emergency response. To address the low response efficiency and insufficient service coverage of existing emergency rescue networks in mountainous regions, it is essential to construct networks that balance redundancy and efficiency. This study took the western mountainous areas of Beijing and surrounding townships as the study area and developed a multi-objective optimization model under limited resource conditions. The model simultaneously minimizes three objectives: maximum response time, population-weighted average response time, and maximum backup response time. A redundancy constraint requiring each township to be covered by at least two Emergency Rescue Centers (ERCs) is incorporated, together with facility capacity constraints and service disparity control. The model is solved using the NSGA-II algorithm to derive optimal network configurations. Travel time estimated from online map services during typical peak-hour periods and township-level census population data are used as empirical inputs. To evaluate the stability of the optimization results, each scenario is independently solved using 30 different random seeds, and the resulting solution sets are examined via the Kruskal-Wallis non-parametric test. Four comparative scenarios are designed: the baseline network comprising 13 existing ERCs (G1), and three scenarios involving the addition of a single ERC at Zhaitang Township (G2), Donghuayuan Township (G3), and Sanpo Township (G4), respectively. The optimization results are analyzed through Pareto front comparison and scenario-based evaluation, focusing on response efficiency, redundancy performance, and network structural characteristics. The results indicate that G2 (Zhaitang) primarily strengthens redundancy coverage in deep mountainous areas by expanding backup service pathways, thereby enhancing service equity. G4 (Sanpo) achieves the most substantial reduction in maximum response time, decreasing it by 23.1% relative to the baseline, and demonstrates the strongest robustness under ERC-failure scenarios. G3 (Donghuayuan) yields comparatively limited improvement across all evaluation dimensions. Furthermore, network structure analysis reveals that although adding new ERCs does not fundamentally alter the overall network backbone, the strategic placement of new nodes can effectively reshape the redundancy-efficiency trade-off boundary. This study demonstrates that targeted node addition to an existing network constitutes a key pathway for enhancing system resilience and provides an extensible methodological framework for optimizing emergency rescue network configurations in mountainous regions under complex terrain conditions.

Strategic emerging industries, as an important component of new quality productive forces, serve as a key pillar of the modern industrial system and a significant driving force for the Chinese-style modernization. Based on data from Chinese listed companies in strategic emerging industries and their investment-related enterprises, this study systematically analyzed the development trends, spatial pattern changes, and regional division of labor and collaboration patterns of related enterprises in China's strategic emerging industries from the end of the 13th Five-Year Plan period to the end of the 14th Five-Year Plan period. The study revealed that during the 14th Five-Year Plan period, China's strategic emerging industries maintained a positive development trend, particularly standing out during the economic recovery phase in the post-pandemic era. From an industry perspective, related enterprises in strategic emerging industries have increasingly concentrated in key areas such as manufacturing, research and development, business, and finance, while spatially further clustering in major urban agglomerations, including the Beijing-Tianjin-Hebei region, the Yangtze River Delta area, the Pearl River Delta area, Chengdu-Chongqing, and the middle reaches of the Yangtze River, as well as some key provincial capital cities. This has formed an overall pattern centered around the five major urban agglomerations. Both spatial distance and hierarchical distance have imposed constraints on the spatial expansion of strategic emerging industries, and spatial distance played a stronger constraining role. Significant differences existed between different industries within this framework. From the perspective of factors influencing the spatial layout of related enterprises in strategic emerging industries, the entire industries generally tended to locate in areas with a high concentration of core enterprises and their associated businesses, showing a preference for cities with advanced industrial structures. However, spatial layout preferences varied across specific types of industries.

Under the requirements of high-quality development, optimizing and evaluating land resource allocation in resource-based ecologically fragile regions is key to achieving coordinated economic, social, and ecological development. Taking the Lunan Economic Circle as an example, the multi-objective optimization algorithm and entropy-weight TOPSIS were employed to determine the quantitative optimization scheme of land use in 2030; the PLUS model was employed to predict the optimized spatial layout of land use; and the SBM model was employed to measure the multi-period ecological efficiency to quantitatively evaluate the reliability of land use optimization results. The results show that: 1) With the rigid constraint of the arable land red line, although the acreage of arable land in the region decreases by 2030, it remains above the safety baseline, while the areas of construction land, forest land, grassland, and water bodies increase, achieving optimization of total land use and structure. 2) After optimization, scattered arable land is converted to construction land; sloping arable lands in the Yishan-Mengshan-Nishan area are restored to forest and grassland; the wetland ecological space of the Nansi Lake expands; and unused land near mountains and suburbs is orderly developed, resulting in a more rational spatial pattern. 3) After optimization, as the area of ecological land expands, the gross ecosystem product of all counties is improved, and the overall ecological efficiency of the region will improve from 0.29 in 2020 to 0.33 after optimization in 2030, with further reduction in regional disparities. In conclusion, multi-objective optimization considering the economic-social-ecological functions of land can effectively allocate land resources, promote the ecological transition of these resource-based ecologically fragile regions, and accelerate regional sustainable development.

As the digital economy expands, rural tourism micro-enterprises (RTMEs) face challenges in both digital transformation and resilience building. Digital literacy, a key driver of digitalization, is crucial for fostering innovation and resilience, but the mechanisms behind its impact remain unclear. This study investigated how digital literacy influences innovation and resilience in RTMEs, with a particular focus on the mediation role of innovation. Using a mixed-methods approach combining fsQCA and regression analysis, the study surveyed 72 RTMEs from Shuanglang and Wenlin Villages in Yunnan Province, China. A complex mediation model of "digital literacy-innovation vitality-resilience" was proposed. The fsQCA identified key digital literacy configurations, while regression analysis examined their direct and indirect effects on resilience. The findings show that: 1) Five distinct digital literacy configurations foster high innovation vitality, forming a "perception-capture-transformation" chain with multiple equivalent pathways. 2) Innovation vitality acts as a complex mediator between digital literacy and resilience, with some configurations promoting resilience and others hindering it. 3) Digital literacy dimensions are dynamically complementary, with digital survival skills being crucial for aligning innovation and resilience. Without these skills, misalignment between the two occurs. This study provides a theoretical framework for understanding digital literacy's role in enhancing resilience and offers practical recommendations for RTMEs to optimize their digital capabilities. By identifying context-specific pathways, it suggests tailored strategies for sustainable development in rural tourism.

As a core element of urban environments, the vitality of public green spaces serves as a key indicator for measuring the efficiency of urban environmental services and residents' well-being. This study took 93 public green spaces in the main urban area of Nanjing City as empirical cases. It integrated multi-source heterogeneous data, including Baidu Huiyan population location data, street view images, points-of-interest (POIs), road networks, and social media photographs. By comprehensively applying geographic detector analysis, the multi-scale geographically weighted regression (MGWR) model, and the four-quadrant analysis method, the study innovatively constructed a park green space vitality analysis framework based on the interaction between subjective and objective environments from both the global and local perspectives. This enables a multi-scale analysis of the spatiotemporal differentiation characteristics and underlying causes of public green space vitality in Nanjing City. The findings reveal that: 1) The vitality of Nanjing's public green spaces exhibits significant spatial differentiation, presenting a gradient pattern characterized by high-vitality clustering in the central-eastern areas and low-vitality diffusion in the periphery. 2) Globally, user preferences for service facilities and green view index are the core drivers explaining green space vitality, with notable coupling effects among factors. 3) Locally, the influencing mechanisms of green space vitality display significant spatial heterogeneity, with high variability in factors such as service facilities, decorative elements, and functional mix, while the impacts of functional density and infrastructure remain relatively stable. 4) The differentiated synergy of four key factors—transport accessibility, functional configuration, streetscape, and user visual preferences—proves effective in enhancing public green space vitality. The theoretical framework developed in this study implements an analytical strategy of multi-scale diagnosis-spatial differentiation identification-targeted regulation, providing policymakers with scientific tools including hotspot identification, deficiency diagnosis, and intervention priority assessment to support precision planning strategies based on spatial heterogeneity.

Traffic collisions present a global public safety challenge, and they arise from the combined effects of human, vehicle, road, and environment factors within urban transportation systems. While existing studies have predominantly focused on the impact of the built environment on traffic collisions, limited attention has been given to travelers' subjective perception of safety and its interaction with road network characteristics. Using street links in the main urban area of Wuhan City as the basic unit of analysis, this study employed street view imagery and machine learning techniques to evaluate perceived safety at the street link level. Using a four-way decomposition model, we quantitatively analyzed the controlled direct effect (CDE), the reference interaction without mediation (INT_ref), the pure mediated effect (PIE), and the mediated interaction (INT_med) through which road network characteristics influence traffic collisions via perceived safety. The results show a significant correlation between perceived safety and traffic collisions, indicating the presence of a "perception bias". Furthermore, topological and geometric characteristics of road networks influence traffic collisions through both the CDE and the PIE mediated by perceived safety. Betweenness centrality, diversion ratio, and mean geodesic length also affect traffic collisions through INT_ref and INT_med with perceived safety, whereas the near-line ratio operates through INT_ref with perceived safety. Among these pathways, the CDE plays the dominate role, while INT_ref, PIE, and INT_med contribute minor proportions, demonstrating that perceived safety moderates the magnitude but not the direction of the total effect. The findings elucidate the complex mechanisms by which urban road network characteristics affect traffic collisions from the perspective of perceived safety, providing a theoretical basis for developing road safety design strategies that integrate both objective and subjective considerations.

Against the backdrop of global poverty reduction and China's efforts to consolidate the achievements of poverty alleviation, transport-related social exclusion in mountainous rural areas—stemming from geographic and individual factors—has emerged as a significant determinant of relative poverty. Taking Huangping County in Guizhou Province as a case study and drawing on household survey data from 2019, this study constructed a measurement framework for transport-related social exclusion and employed a binary logit model to empirically analyze its relationship with relative poverty. The results reveal that: 1) Physical disability and lack of motor vehicles were key drivers of relative poverty, as they respectively undermined labor capacity and restricted spatial mobility, thereby exacerbating barriers to social participation. 2) There was marked heterogeneity among different groups regarding the impact of transport disadvantages. Males, individuals of working age, and those with only primary education were more sensitive to disability and lack of transport means, reflecting the high dependence of productive and employment activities on transportation. 3) For groups with junior high school education and above, relative poverty was constrained by a diverse set of factors, including subjective health, transport expenditure, and travel safety, indicating a shift in multidimensional development needs as education levels rise. 4) Frequent travels to the county seat were negatively correlated with relative poverty, suggesting that active integration into the regional economic network can effectively reduce the risk of relative poverty. This study demonstrated that social exclusion and mobility constraints arising from transport disadvantages are important triggers of relative poverty in contemporary mountainous rural areas. The research expanded the micro-level perspective of transport-led poverty reduction, confirmed the role of transport-related social exclusion in the formation of relative poverty, and provided a scientific basis for precisely identifying impoverished groups and formulating differentiated policies.

Tunpu culture in Central Guizhou is a unique regional cultural phenomenon. This study focused on 37 Tunpu traditional villages in Anshun City, Guizhou Province, and their intangible cultural heritage (ICH) projects at or above the provincial level, using a comprehensive evaluation model, a factor contribution model, and the kernel density estimation method to evaluate the living state of ICH within these villages. Furthermore, it identified the types of the living state of ICH in villages and revealed corresponding spatial distribution patterns. The results show that: 1) The overall living state of ICH in Tunpu traditional villages is suboptimal, with pronounced polarization across different dimensions. 2) Anshun Dixi Opera exhibits the highest levels in both its living state and stability among the individual ICH projects, and the largest number of villages in the study area have advantages in the living state of performance ICH. 3) The types of the living state of ICH in Tunpu traditional villages are classified as: synergistic advantage, characteristic agglomeration, potential activation, enhancement driven, restoration and improvement, and adjustment and restructuring. Spatially, the high-density core area is located at the border between Xixiu and Pingba districts. 4) Overall, the average living state of ICH in Tunpu traditional villages is higher in Xixiu District than in Pingba District. The research results are in line with the actual situation, and provide a scientific basis for the sustainable development of ICH in Tunpu traditional villages.

Amid accelerating global population aging, elderly sojourn behavior has emerged as a critical phenomenon with profound socioeconomic implications. The geographic mobility patterns and settlement intentions of elderly sojourners are reshaping urban demographic landscapes and recalibrating public resource allocation dynamics, posing novel governance challenges for destination cities. This study used Sanya City (China's premier tropical coastal retirement destination) as a representative case to investigate elderly sojourn dynamics through a tripartite analytical framework. Using origin-destination (O-D) matrix analysis based on elderly preferential travel card data (2016-2020), we first delineated the spatiotemporal change of elderly sojourners' mobility patterns. Subsequently, multilevel logistic regression models based on the 2021 questionnaire survey data (N=150) revealed determinants of their settlement intentions. Finally, we put forward differentiated governance strategies. The results show that: 1) There was a phased spatial progression characterized by Northeast China dominance (51.17% of elderly sojourners)-regional node expansion-nationwide dispersion-COVID-19 induced contraction, and the migration showed a seasonal tidal effect, with the majority of the migrant population aged 65-75 years. 2) Elderly sojourners in Sanya demonstrated higher education level and family disposable income, typically accompanied by a spouse and suffering from chronic diseases. Their settlement intention was significantly affected by family factors, migration patterns, and community environment. Those in the family-oriented migration and long-term migration categories had a higher probability of settling down, while a housing area exceeding 65 m² and a residence adjacent to hospitals can significantly improve their willingness to stay. 3) Based on migration cycles and settlement intentions, elderly sojourners were categorized into four groups: seasonal long-term sojourners, seasonal short-term sojourners, permanent long-term sojourners, and permanent short-term sojourners. This research expanded the theoretical framework of elderly sojourn research through its multiscalar methodology integrating macro-scale mobility mapping with micro-level behavioral analysis, offering evidence-based policy recommendations for elderly sojourner-responsive urban governance. The findings particularly inform destination cities' strategies for joint management mechanism, seasonal infrastructure management, and differentiated community services tailored to elderly sojourn characteristics in aging societies.

In recent years, extreme weather events are increasingly frequent, severely impacting human mobility and socioeconomic activities. Ensuring the robustness of intra-city mobility is essential for the development of resilient cities. However, existing studies primarily focused on physical infrastructure or routine mobility patterns, with insufficient understanding of the spatial mechanisms of human mobility changes under external disturbances. This study constructed the "weather-environment-behavior" framework by combining spatial behavior and disaster risks. Based on mobile phone signaling data, the spatiotemporal characteristics of human mobility in Shanghai under the influence of Typhoon Bebinca are identified, and the driving mechanisms including weather conditions, traffic environment, built environment, and socioeconomic factors are analyzed through geographically weighted regression (GWR). Key findings include: 1) Human mobility in Shanghai was severely impacted during the typhoon and lasted for a long time, showing a clear "decline-recovery" process and rebound after the disaster. Mobility intensity showed negative correlation with weather conditions in time series. 2) Mobility patterns showed ring-shaped spatial differentiation, with the central urban area and distant suburbs experiencing severe fluctuations and impacts, while the near suburbs were less affected. In temporal terms, the central urban area exhibited gradual response patterns, while the peripheral area exhibited sensitive response patterns. 3) Changes of mobility were influenced by different factors in a spatially non-stationary manner: central urban areas were primarily affected by rainfall duration and travel distance, suburban areas were primarily affected by travel intensity and land use mix, while remote suburban areas were influenced by factors including transportation infrastructure, land use functions, and public service levels. Socioeconomic factors contributed to shock mitigation in most peripheral areas. It will be helpful to enhance the adaptability of the city by alleviating overcrowding in urban centers, defining the dominant functions of new towns, increasing employments, and improving infrastructures. This study aimed to provide a scientific basis for urban planning, traffic management, and emergency response, promoting urban safety, resilience, and sustainable development.

In the era of financialization turn, high-end financial service capabilities with high professionalism and high added value have become one of the core competencies for cities to participate in regional capital allocation. However, most of the existing studies measure urban financial service capabilities within the framework of static analysis, lacking a dynamic network perspective based on the actual financial connections between cities and attention to the high-end financial service capabilities of cities. This study overcome some limitations of the traditional network construction methods by focusing on the relationship between listed enterprises and related advanced producer services (APS) during the initial public offering (IPO) process of listed enterprises. The study incorporated the IPO-raised funds into the weight to construct a multi-stage high-end financial service network for Chinese cities from 1993 to 2023. The social network analysis method was adopted to measure and evaluate the high-end financial service capabilities of cities, and the formation mechanism was systematically analyzed in combination with the bidirectional fixed effects model. The research findings are as follows: 1) The urban financial network in China presented a hierarchical core-periphery structure and a spatial pattern of dense in the east and sparse in the west, and the regional network pattern was consistent with the overall economic development level. 2) The high-end financial service capabilities of Chinese cities presented a core-periphery structure centered on Beijing-Shanghai-Shenzhen, and polarization was increasingly prominent over time. 3) The empirical results based on the "input-demand-institutional" analysis framework reveal the core formation mechanism of a city's high-end financial service capacity: The reserve of financial industry talents enhances the quality of high-end service supply by increasing a city's human capital, and the city's innovation capacity mainly plays a role by driving the demand for high-end financial services through the listing of science and technology innovation enterprises. The administrative hierarchy of cities promotes the aggregation of elements and the construction of an innovative ecosystem through institutional empowerment in large cities, indirectly driving capacity improvement. The dynamic weighted network method developed in this research overcome the limitations of traditional frequency statistics, more scientifically and comprehensively revealing the spatial pattern of high-end financial service capabilities in Chinese cities, and provides a solid empirical basis for understanding its formation mechanism.

Declining resource-based cities, as "problem regions" in China's regional development, have seen cross-regional investment becoming an important means to accelerate inter-regional flows of production factors and promote their own transformation and development with the reduction of their comparative advantages. Based on data of cross-regional investments by enterprises in China's declining resource-based cities from 2001 to 2022, this study analyzed the characteristics of investment scales, investment distances, and investment field characteristics, adopted the social network analysis method to analyze the evolution trend of the cross-regional investment networks by enterprises, and further examined the influencing factors from both the push and pull perspectives. The results show that: 1) The scale of cross-regional investment by enterprises in China's declining resource-based cities gradually increased from 2001 to 2022, and cities in central China gradually became the main cross-regional investment subjects. There was a significant local preference in the process of enterprise cross-regional investment, but medium and long-distance investments had increased in recent years, showing the feature of "contraction at both ends and expansion in the middle". 2) Manufacturing and producer services were not only the main sectors for outward investment but also key recipient sectors. Over time, the invested producer services had experienced obvious changes from wholesale and retail trade to scientific research and technical services. 3) The complexity and intensity of the enterprise cross-regional investment network continued to increase; however, the spatial structure remained relatively decentralized, with weak connections between cities. During the study period, the polarization of the strongest ties had weakened, and structural adjustment within the network was evident. 4) The enterprise cross-regional investment network exhibited a significant modular structure, with new nodes increasingly integrating through cross-module collaboration, highlighting a growing hierarchical trend. Additionally, the enterprise cross-regional investment network was transitioning from a distinct core-periphery structure towards a more balanced state. 5) The influencing factors varied significantly across different stages. The economic vitality of declining resource-based cities and the geographical distance between the investing and receiving cities consistently remained the primary factors affecting cross-regional investment by enterprises. This study contributes to a deeper understanding of the spatial structure and key influencing factors of enterprise cross-regional investment in declining resource-based cities, providing a scientific support for optimizing the path selection and decision making of cross-regional investment and promoting regional coordinated development. The research findings may serve as a reference for other types of resource-based cities.

Knowledge complexity is a core variable for assessing regional innovation quality and predicting economic growth potential, yet existing studies have insufficiently examined its spatiotemporal heterogeneity and driving mechanisms at micro scales such as towns and subdistricts. Drawing on invention patent data for township‑level units (towns and subdistricts) in the Pearl River Delta region from 1990 to 2022, this study measured the knowledge complexity index (KCI) and, by combining spatial autocorrelation analysis with a multi‑scale geographically weighted regression (MGWR) model, explored the spatiotemporal dynamics of knowledge complexity. The results show that: 1) The overall change of knowledge domains followed a pattern of "ICT‑led and multi‑field synergy", while knowledge domains in strategic emerging industries such as biomedicine and new energy exhibited breakthrough spatial configurations. 2) The spatial pattern of knowledge complexity followed a gradient of "core agglomeration and peripheral lag", evolving from an initially scattered distribution into a polycentric network structure centered on the Guangzhou-Shenzhen science and technology innovation corridor. 3) The driving effects of knowledge structure displayed pronounced spatiotemporal heterogeneity, with related variety continuously strengthening the positive impact of technological relatedness on knowledge complexity, whereas unrelated variety showing a stage‑specific trajectory of first promoting and then differentiation—exerting a generally positive effect on knowledge complexification in the early period, but in the later period remaining significantly positive only in the Guangzhou-Foshan core area. 4) The spatial configuration of innovation factors played a key role in shaping the differentiation of knowledge complexity. Local governments need to adopt gradient‑adaptive strategies: core areas should reinforce networks of technological relatedness, while peripheral areas should prioritize the cultivation of specialized cluster advantages. This study can provide scientific references for breaking low‑end lock‑in, reshaping a high‑quality innovation landscape, and constructing spatial coordination mechanisms in the Pearl River Delta region.

Against the backdrop of technological revolution reshaping regional development patterns, the Nanjing Metropolitan Area—a key hub for the Yangtze River Delta's influence on central and western China—plays a crucial role in regional high-quality development through its innovation integration. This study used high-tech corporate investment, talent mobility, and county patent transfer data from 2000 to 2023 to construct a multidimensional innovation network for the Nanjing Metropolitan Area. Employing complex network analysis, the siphoning and trickle-down model, and the quadratic assignment procedure (QAP) regression method, it systematically explored the structural change, spatial effects, and driving mechanisms of this innovation system. The results show that: 1) The innovation network exhibited a spatial radiation pattern centered on Nanjing. The siphoning and trickle-down effect of the Nanjing growth pole has shifted from strong siphoning-weak trickling to collaborative development. Technology flows have transitioned from siphoning to trickling dominance, capital flows continued to spill over, and talent siphoning intensity has decreased. 2) Adjacent counties and districts of prefecture-level cities are categorized into five types of border effects: shielding, penetration, contact, filtering, and integration. Nanjing-Ma'anshan and Wuhu-Xuancheng formed technology flow integration boundaries, while Changzhou-Xuancheng and Nanjing-Yangzhou exhibited talent flow integration boundaries; Some boundaries between Nanjing-Zhenjiang and Nanjing-Chuzhou exhibited filtering effects on capital flows due to administrative gradient differences, specifically manifested as high-intensity innovation diffusion from Nanjing to Jurong, Nanqiao, and Lai'an. 3) Economic development and enterprise development levels exerted differentiated influences on multidimensional innovation linkages across different periods. Labor income disparities exhibited a significant negative correlation with innovation linkages, while fiscal science and technology investments, development zones, and the number of universities significantly promoted innovation linkages. Geographic, technological, and institutional proximity facilitated factor mobility. This study revealed the complex mechanisms underlying innovation integration within the Nanjing Metropolitan Area from the perspective of multidimensional innovation networks, aiming to provide a theoretical foundation and practical reference for regional collaborative innovation development.

This study analyzed the spatial flow path of carbon sequestration services based on the flow of ecosystem services, and constructed a one-to-one carbon compensation mechanism linking the subject and object of compensation, to provide a theoretical reference and scientific support for optimizing the carbon compensation policy for the coordinated development of the ecology and economy. Taking the Yangtze River Delta (YRD) urban agglomeration as the study area, the study clustered the standard explicit comparative advantages in the socioeconomic, ecological environment, and land use structure aspects, identified carbon compensation and compensated areas, revealed the spatial transfer paths of carbon sequestration services within the YRD urban agglomeration by combining with the fracture point and field strength model, and then calculated the amount of carbon compensation based on the contribution of carbon sinks of the cities. The results of the study indicate that: 1) Carbon emissions in the YRD urban agglomeration showed a continuous upward trend, while carbon sequestration showed a downward trend. Spatially, carbon emissions and carbon sequestration showed opposite distribution patterns, with carbon emissions characterized by "high in the east, low in the west and high in the north, low in the south" and carbon sequestration characterized by "high in the west, low in the east and high in the south, low in the north". 2) During the study period, the flow of carbon sequestration services in the YRD urban agglomeration was mainly in the direction of southwest-northeast, with a clear preference for proximity, where Xuancheng was the most stable and largest carbon sequestration service output area, and Nanjing (adjacent to Xuancheng) was the largest input area. In 2022, the carbon compensation payment of Nanjing was 41036500 yuan. In conclusion, the scale of carbon deficits in the YRD urban agglomeration has been expanding, and there was an obvious spatial mismatch between carbon revenues and expenditures, so the construction of a cross-regional carbon compensation mechanism is a realistic demand for realizing the dual carbon goals.

Against the backdrop of evolving regional population mobility patterns and spatial transformations from urbanization, county-level units in inland regions of China have emerged as significant arenas for nearby urbanization in recent years. This study developed an indicator for the propensity of intra-county mobility. It employed a coupling and coordination degree model and an evaluation method for coordination influence to investigate the evolution of the preference for localized population mobility in counties within central China from 2010 to 2020, along with its coupling and coordination relationship with multi-dimensional urbanization at the county level. The findings reveal that: 1) Population mobility in these counties was characterized by a dominance of long-distance migration alongside an accelerated trend towards nearby movement. Differences in mobility choices appeared across provinces, influenced by their varying stages of economic development. The gap in the preference for intra-county mobility between regular counties and county-level cities was minimal, underscoring the fundamental role of county seats in absorbing locally oriented population flows. 2) The coupling and coordination between the preference for intra-county mobility and demographic urbanization was generally high. The most notable improvement was observed in the coordination with social urbanization. However, the economic subsystem had begun to show an inhibiting effect on the overall coupling degree. The dominant influence on coordination imbalance was shifting away from being primarily driven by the social service system towards being increasingly constrained by lagging economic development. 3) The differentiation of county types and the evolution of their multi-dimensional coupling relationships resulted from the combined effects of local retention forces and external pull factors. Government initiatives, through institutional innovation and improved public services, strengthened local retention and promoted coordinated development between intra-county mobility and social urbanization. Nonetheless, the relative lag in the supply of industrial factors led to an absence of production-oriented pull forces. This, combined with the persistent effect of external pull factors, created a constraining effect from the economic subsystem and introduced risks associated with exogenous urbanization. This research deepens the understanding of the change of population mobility patterns and the mechanisms underlying county urbanization pathways. It can provide a reference for promoting healthy and sustainable nearby urbanization.